3-generation family medical histories of mental, neurologic, cardiometabolic, birth defect, asthma, allergy, and autoimmune conditions associated with autism.

Background: Family histories of different mental and non-mental conditions have often been associated with autism spectrum disorder (ASD) but the restricted scope of conditions and family members that have been investigated limits etiologic understanding. We aimed to perform a comprehensive assessment of ASD associations with 3-generation family histories of 90 mental, neurologic, cardiometabolic, birth defect, asthma, allergy, and autoimmune conditions. The assessment comprised separate estimates of association with ASD overall; separate estimates by sex and intellectual disability (ID) status; as well as separate estimates of the co-occurrence of each of the 90 disorders in autistic persons. Additionally, we aimed to provide interactive catalogues of results to facilitate results visualization and further hypothesis-generation. Methods: We conducted a population-based, registry cohort study comprised of all live births in Denmark, 1980-2012, of Denmark-born parents, and with birth registry information (1,697,231 births), and their 3-generation family member types (20 types). All cohort members were followed from birth through April 10, 2017 for an ASD diagnosis. All participants (cohort members and each family member) were followed from birth through April 10, 2017 for each of 90 diagnoses, emigration or death. Adjusted hazard ratios (aHR) were estimated for ASD overall; by sex; or accounting for ID via separate Cox regression models for each diagnosis-family member type combination, adjusting for birth year, sex, birth weight, gestational age, parental ages at birth, and number of family member types of index person. aHRs were also calculated for sex-specific co-occurrence of each disorder, for ASD overall and considering ID. A catalogue of all results is displayed via interactive heat maps here: https://ncrr-au.shinyapps.io/asd-riskatlas/ and interactive graphic summaries of results are here: https://public.tableau.com/views/ASDPlots_16918786403110/e-Figure5. Results: Increased aHRs for ASD (26,840 cases; 1.6% of births) were observed for almost all individual mental disorder-family member type combinations yet for fewer non-mental disorder-family member type combinations. aHRs declined with diminishing degree of relatedness between the index person and family member for some disorders, especially mental disorders. Variation in aHR magnitude by family member sex (e.g., higher maternal than paternal aHRs) or side of the family (e.g., higher maternal versus paternal half sibling aHRs) was more evident among non-mental than mental disorders. Co-occurring ID in the family member or the index person impacted aHR variation. Conclusion: Our approach revealed considerable breadth and variation in magnitude of familial health history associations with ASD by type of condition, sex of the affected family member, side of the family, sex of the index person, and ID status which is indicative of diverse genetic, familial, and non-genetic ASD etiologic pathways. More careful attention to identifying sources of autism likelihood encompassed in family medical history, in addition to genetics, may accelerate understanding of factors underlying neurodiversity.

Racialized experience, biomarkers of lead exposure, and later-life cognition: a mediation analysis.

We evaluated the role of the neurotoxicant lead (Pb) in mediating racial disparities in later-life cognition in 1,085 non-Hispanic Black and 2,839 non-Hispanic white participants in NHANES (1999-2002, 2011-2014) 60+ years of age. We operationalized Black race as a marker for the experience of racialization and exposure to systemic racism. We estimated patella bone Pb via predictive models using blood Pb and demographics. Concurrent cognition (processing speed, sustained attention, working memory) was measured by the Digit Symbol Substitution Test (DSST) and a global measure combining four cognitive tests. To obtain the portion mediated, we used regression coefficients (race on Pb * Pb on cognitive score)/(race on cognitive score), adjusting for age, NHANES cycle, and sample weights. Other confounder adjustment (education, poverty income ratio, smoking) was limited to the mediator-outcome (i.e., Pb-cognition) pathway because these factors do not lie upstream of race and so cannot confound associations with race. Pb was estimated to mediate 0.6% of the association between race and global cognition, and 4% of the DSST. Our results suggest that later-life cognitive health disparities may be impacted by avoidable lead exposure driven by environmental injustice, noting that a large proportion of the pathway of systemic racism harming cognition remains.

Association between objective measures and parent-reported measures of child tobacco smoke exposure: A secondary data analysis of four trials.

INTRODUCTION: Tobacco smoke exposure (TSE) harms children and adults. Studies of childhood TSE exposure often relies on parental reports, but may benefit from objective measures. The objective of our study was to study the relationship between reported and objective measures of TSE. METHODS: We analyzed data from four intervention trials, conducted in clinical or community settings, to identify objective measures most closely associated with parent-reported measures and the optimal set of parent-reported measures for predicting objective measures. We also assessed whether there was a learning curve in reported exposure over time, and the importance of replicate biomarker measures. RESULTS: Correlations between objective and parent-reported measures of child TSE were modest at best, ranging from zero to 0.41. Serum cotinine and urinary cotinine were most strongly associated with parental reports. Parental questions most closely related to biomarkers were number of cigarettes and home smoking rules; together these formed the best set of predictive questions. No trial included all objective measures and all questions, precluding definitive statements about relative advantages. Within-subject repeatability of biomarker measures varied across studies, suggesting that direct pilot data are needed to assess the benefit of replicate measurements. CONCLUSIONS: Improvements in objective and parent-reported child exposure measurements are needed to accurately monitor child TSE, evaluate efforts to reduce such exposure, and better protect child health.

A New Combined Air Quality and Heat Index in Relation to Mortality in Monterrey, Mexico.

The negative synergistic effects of air pollution and sensible heat on public health have been noted in numerous studies. While separate, simplified, and public-facing indices have been developed to communicate the risks of unhealthful levels of air pollution and extreme heat, a combined index containing elements of both has rarely been investigated. Utilizing air quality, meteorology, and mortality data in Monterrey, Mexico, we investigated whether the association between the air quality index (AQI) and mortality was improved by considering elements of the heat index (HI). We created combined indices featuring additive, multiplicative, and either/or formulations and evaluated their relationship to mortality. Results showed increased associations with mortality for models employing indices that combined the AQI and the HI in an additive or multiplicative manner, with increases in the interquartile relative risk of 3-5% over that resulting from models employing the AQI alone.

Maternal smoking during pregnancy and offspring intellectual disability: sibling analysis in an intergenerational Danish cohort.

BACKGROUND: Maternal smoking has known adverse effects on fetal development. However, research on the association between maternal smoking during pregnancy and offspring intellectual disability (ID) is limited, and whether any associations are due to a causal effect or residual confounding is unknown. METHOD: Cohort study of all Danish births between 1995 and 2012 (1 066 989 persons from 658 335 families after exclusions), with prospectively recorded data for cohort members, parents and siblings. We assessed the association between maternal smoking during pregnancy (18.6% exposed, collected during prenatal visits) and offspring ID (8051 cases, measured using ICD-10 diagnosis codes F70-F79) using logistic generalised estimating equation regression models. Models were adjusted for confounders including measures of socio-economic status and parental psychiatric diagnoses and were adjusted for family averaged exposure between full siblings. Adjustment for a family averaged exposure allows calculation of the within-family effect of smoking on child outcomes which is robust against confounders that are shared between siblings. RESULTS: We found increased odds of ID among those exposed to maternal smoking in pregnancy after confounder adjustment (OR 1.35, 95% CI 1.28-1.42) which attenuated to a null effect following adjustment for family averaged exposure (OR 0.91, 95% CI 0.78-1.06). CONCLUSIONS: Our findings are inconsistent with a causal effect of maternal smoking during pregnancy on offspring ID risk. By estimating a within-family effect, our results suggest that prior associations were the result of unmeasured genetic or environmental characteristics of families in which the mother smokes during pregnancy.

Evaluating the interrelations between the autism polygenic score and psychiatric family history in risk for autism.

Psychiatric family history or a high autism polygenic risk score (PRS) have been separately linked to autism spectrum disorder (ASD) risk. The study aimed to simultaneously consider psychiatric family history and individual autism genetic liability (PRS) in autism risk. We performed a case-control study of all Denmark singleton births, May 1981-December 2005, in Denmark at their first birthday and a known mother. Cases were diagnosed with ASD before 2013 and controls comprised a random sample of 30,000 births without ASD, excluding persons with non-Denmark-born parents, missing ASD PRS, non-European ancestry. Adjusted odds ratios (aOR) were estimated for ASD by PRS decile and by psychiatric history in parents or full siblings (8 mutually-exclusive categories) using logistic regression. Adjusted ASD PRS z-score least-squares means were estimated by psychiatric family history category. ASD risk (11,339 ASD cases; 20,175 controls) from ASD PRS was not substantially altered after accounting for psychiatric family history (e.g., ASD PRS 10th decile aOR: 2.35 (95% CI 2.11-2.63) before vs 2.11 (95% CI 1.91-2.40) after adjustment) nor from psychiatric family history after accounting for ASD PRS (e.g., ASD family history aOR: 6.73 (95% CI 5.89-7.68) before vs 6.32 (95% CI 5.53-7.22) after adjustment). ASD risk from ASD PRS varied slightly by psychiatric family history. While ASD risk from psychiatric family history was not accounted for by ASD PRS and vice versa, risk overlap between the two factors will likely increase as measures of genetic risk improve. The two factors are best viewed as complementary measures of family-based autism risk. LAY SUMMARY: Autism risk from a history of mental disorders in the immediate family was not explained by a measure of individual genetic risk (autism polygenic risk score) and vice versa. That is, genetic risk did not appear to overlap family history risk. As genetic measures for autism improve then the overlap in autism risk from family history versus genetic factors will likely increase, but further study may be needed to fully determine the components of risk and how they are inter-related between these key family factors. Meanwhile, the two factors may be best viewed as complementary measures of autism family-based risk.

Bayesian G-Computation for Estimating Impacts of Interventions on Exposure Mixtures: Demonstration With Metals From Coal-Fired Power Plants and Birth Weight.

The importance of studying the health impacts of exposure mixtures is increasingly being recognized, but such research presents many methodological and interpretation difficulties. We used Bayesian g-computation to estimate effects of a simulated public health action on exposure mixtures and birth weights in Milwaukee, Wisconsin, in 2011-2013. We linked data from birth records with census-tract-level air toxics data from the Environmental Protection Agency's National Air Toxics Assessment model. We estimated the difference between observed and expected birth weights that theoretically would have followed a hypothetical intervention to reduce exposure to 6 airborne metals by decommissioning 3 coal-fired power plants in Milwaukee County prior to 2010. Using Bayesian g-computation, we estimated a 68-g (95% credible interval: 25, 135) increase in birth weight following this hypothetical intervention. This example demonstrates the utility of our approach for using observational data to evaluate and contrast possible public health actions. Additionally, Bayesian g-computation offers a flexible strategy for estimating the effects of highly correlated exposures, addressing statistical issues such as variance inflation, and addressing conceptual issues such as the lack of interpretability of independent effects.

Prediction of Autism Risk From Family Medical History Data Using Machine Learning: A National Cohort Study From Denmark.

Background: A family history of specific disorders (e.g., autism, depression, epilepsy) has been linked to risk for autism spectrum disorder (ASD). This study examines whether family history data could be used for ASD risk prediction. Methods: We followed all Danish live births, from 1980 to 2012, of Denmark-born parents for an ASD diagnosis through April 10, 2017 (N = 1,697,231 births; 26,840 ASD cases). Linking each birth to three-generation family members, we identified 438 morbidity indicators, comprising 73 disorders reported prospectively for each family member. We tested various models using a machine learning approach. From the best-performing model, we calculated a family history risk score and estimated odds ratios and 95% confidence intervals for the risk of ASD. Results: The best-performing model comprised 41 indicators: eight mental conditions (e.g., ASD, attention-deficit/hyperactivity disorder, neurotic/stress disorders) and nine nonmental conditions (e.g., obesity, hypertension, asthma) across six family member types; model performance was similar in training and test subsamples. The highest risk score group had 17.0% ASD prevalence and a 15.3-fold (95% confidence interval, 14.0-17.1) increased ASD risk compared with the lowest score group, which had 0.6% ASD prevalence. In contrast, individuals with a full sibling with ASD had 9.5% ASD prevalence and a 6.1-fold (95% confidence interval, 5.9-6.4) higher risk than individuals without an affected sibling. Conclusions: Family history of multiple mental and nonmental conditions can identify more individuals at highest risk for ASD than only considering the immediate family history of ASD. A comprehensive family history may be critical for a clinically relevant ASD risk prediction framework in the future.

Associations Between Early Low-Level Tobacco Smoke Exposure and Executive Function at Age 8 Years.

OBJECTIVE: To investigate whether exposure to tobacco smoke during early brain development is linked with later problems in behavior and executive function. STUDY DESIGN: We studied 239 children in a prospective birth cohort. We measured tobacco exposures by caregiver report and serum cotinine 3 times during pregnancy and 4 times during childhood. We used linear regression to examine the association between prenatal and childhood serum cotinine concentrations and behavior (the Behavior Assessment System for Children-2) and executive function (the Behavior Rating Inventory of Executive Function) at age 8 years while adjusting for important covariates. RESULTS: Neither prenatal nor child serum cotinine were associated with behavior problems measured by the Behavior Assessment System for Children-2. On the Behavior Rating Inventory of Executive Function, prenatal and childhood exposure was associated with poorer task initiation scores (B = 0.44; 95% CI, 0.03-0.85 and B = 0.69, 95% CI, 0.06-1.32 respectively). Additionally, in a subset of 208 children with nonsmoking mothers, prenatal exposure was associated with task initiation scores (B = 1.17; 95% CI, 0.47-1.87) and additional components of the metacognition index (eg, working memory, B = 1.20; 95% CI, 0.34-2.06), but not components of the behavioral regulation index. CONCLUSIONS: Tobacco exposures during pregnancy (including low-level second-hand smoke) and childhood were associated with deficits in some domains of children's executive function, especially task initiation and metacognition. These results highlight that decreasing early exposure to tobacco smoke, even second-hand exposure, may support ideal brain functioning.

Familial confounding of the association between maternal smoking in pregnancy and autism spectrum disorder in offspring.

Evidence supports no link between maternal smoking in pregnancy and autism spectrum disorder (autism) overall. To address remaining questions about the unexplained heterogeneity between study results and the possibility of risk for specific autism sub-phenotypes, we conducted a whole-population cohort study in Denmark. We followed births 1991-2011 (1,294,906 persons, including 993,301 siblings in 728,271 families), from 1 year of age until an autism diagnosis (13,547), death, emigration, or December 31, 2012. Autism, with and without attention deficit hyperactivity disorder (ADHD) and with and without intellectual disability (ID) were based on ICD-8 and ICD-10 codes from Danish national health registers, including 3,319 autism + ADHD, 10,228 autism - no ADHD, 2,205 autism + ID, and 11,342 autism - no ID. We estimated hazard ratios (HRs) and 95% confidence intervals (95% CIs) between any maternal smoking (from birth records) and autism (or sub-phenotypes) using survival models with robust standard errors, stratifying by birth year and adjusting for child sex, parity, and parental age, education, income, and psychiatric history. To additionally address confounding using family designs, we constructed a maternal cluster model (adjusting for the smoking proportion within the family), and a stratified sibling model. Associations with maternal smoking and autism were elevated in conventional adjusted analyses (HR of 1.17 [1.13-1.22]) but attenuated in the maternal cluster (0.98 [0.88-1.09]) and sibling (0.86 [0.64-1.15]) models. Similarly, risks of autism sub-phenotypes with maternal smoking were attenuated in the family-based models. Together these results support that smoking in pregnancy is not linked with autism or select autism comorbid sub-phenotypes after accounting for familial confounding. Autism Res 2020, 13: 134-144. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Smoking during pregnancy has many harmful impacts, which may include harming the baby's developing brain. However, in a study of thousands of families in Denmark, it does not appear that smoking in pregnancy leads to autism or autism in combination with intellectual problems or attention deficits, once you account for the way smoking patterns and developmental disabilities run in families.

Exposure to air pollution in early childhood and the association with Attention-Deficit Hyperactivity Disorder.

BACKGROUND: Exposure to air pollution in early life has been linked to cognitive deficits and adverse neurodevelopmental effects. However, studies examining associations between air pollutants and Attention-Deficit/Hyperactivity Disorder (ADHD) have had conflicting findings. METHODS: Individuals born in Denmark 1992-2007 (n = 809,654) were followed for the development of ADHD from 1997 to 2013. Data on daily concentrations of nitrogen dioxide (NO2) and fine particulate matter (PM2.5) from air-modeling data at a 1 km × 1 km resolution at residences within the first five years of life, was linked with population-based data from the Danish national registers, including data on clinical diagnoses of ADHD. We estimated incidence rate ratios (IRRs) with 95% confidence intervals (CI) for ADHD, according to increases in exposures, adjusting for age, year, sex, and parental education and income. RESULTS: Exposure to NO2 and PM2.5 during early life was associated with a significantly increased risk of ADHD: IRR of 1.38 (Cl: 1.35 to 1.42) per 10 µg/m3 increase in NO2 and an IRR of 1.51 (Cl: 1.41 to 1.62) per 5 µg/m3 increase in PM2.5. In two-pollutant models, the association between NO2 and ADHD did not change (IRR 1.35; 95% CI: 1.31 to 1.39), while the association with PM2.5 was substantially attenuated (IRR 1.07; 95% CI: 0.98 to 1.16), although in stratified models an elevated association with PM2.5 was found in the lowest quintile of NO2 exposure. CONCLUSIONS: In this large nationwide prospective cohort study, residential air pollution exposure, specifically NO2, during early childhood was associated with the development of ADHD, even when adjusted for parental level of income and education.

Early Life Exposure to Air Pollution and Autism Spectrum Disorder: Findings from a Multisite Case-Control Study.

BACKGROUND: Epidemiologic studies have reported associations between prenatal and early postnatal air pollution exposure and autism spectrum disorder (ASD); however, findings differ by pollutant and developmental window. OBJECTIVES: We examined associations between early life exposure to particulate matter ≤2.5 µm in diameter (PM2.5) and ozone in association with ASD across multiple US regions. METHODS: Our study participants included 674 children with confirmed ASD and 855 population controls from the Study to Explore Early Development, a multi-site case-control study of children born from 2003 to 2006 in the United States. We used a satellite-based model to assign air pollutant exposure averages during several critical periods of neurodevelopment: 3 months before pregnancy; each trimester of pregnancy; the entire pregnancy; and the first year of life. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for study site, maternal age, maternal education, maternal race/ethnicity, maternal smoking, and month and year of birth. RESULTS: The air pollution-ASD associations appeared to vary by exposure time period. Ozone exposure during the third trimester was associated with ASD, with an OR of 1.2 (95% CI: 1.1, 1.4) per 6.6 ppb increase in ozone. We additionally observed a positive association with PM2.5 exposure during the first year of life (OR = 1.3 [95% CI: 1.0, 1.6] per 1.6 µg/m increase in PM2.5). CONCLUSIONS: Our study corroborates previous findings of a positive association between early life air pollution exposure and ASD, and identifies a potential critical window of exposure during the late prenatal and early postnatal periods.

Association of childhood blood lead levels with firearm violence perpetration and victimization in Milwaukee.

Childhood lead exposure impairs future decision-making and may influence criminal behavior, but its role in future firearm violence is unclear. Using public health, education, and criminal justice datasets linked at the individual level, we studied a population-based cohort of all persons born between June 1, 1986 and December 31, 2003 with a valid blood lead test before age 6 years and stable Milwaukee residency (n = 89,129). We estimated associations with firearm violence perpetration (n = 553) and victimization (n = 983) using logistic regression, adjusting for temporal trends, child sex, race, and neighborhood socioeconomic status. Increasing risks for firearm violence perpetration and victimization were found in each higher category of blood lead compared to the lowest, after adjusting for confounding. For perpetration, risk ratios (RR) for increasing comparisons of mean blood lead in categories of ≥5 < 10, ≥10 < 20, and ≥20 µg/dL compared to persons with mean blood lead < 5 µg/dL, were: RR 2.3 (95% CI 1.6, 3.3), RR 2.5 (95% CI 1.7, 3.9), and RR 2.8 (95% CI 1.8, 4.4). For victimization, the same increasing categoric comparisons were: RR 1.8 (95% CI 1.4, 2.3), RR 2.4 (95% CI 1.8, 3.2), RR 3.3 (95% CI 2.4, 4.5). The proportion of firearm violence attributable to blood lead ≥5 µg/dL was 56% for perpetration and 51% for victimization. In Milwaukee, during a period of high lead exposures, childhood levels may have substantially contributed to adult firearm violence. While we cannot definitively conclude causality, the possibility that over half of firearm violence among this sample might be due to lead exposure suggests the potential importance of lead exposure reduction in firearm violence prevention efforts.

Air Toxics in Relation to Autism Diagnosis, Phenotype, and Severity in a U.S. Family-Based Study.

BACKGROUND: Previous studies have reported associations of perinatal exposure to air toxics, including some metals and volatile organic compounds, with autism spectrum disorder (ASD). OBJECTIVES: Our goal was to further explore associations of perinatal air toxics with ASD and associated quantitative traits in high-risk multiplex families. METHODS: We included participants of a U.S. family-based study [the Autism Genetic Resource Exchange (AGRE)] who were born between 1994 and 2007 and had address information. We assessed associations between average annual concentrations at birth for each of 155 air toxics from the U.S. EPA emissions-based National-scale Air Toxics Assessment and a) ASD diagnosis (1,540 cases and 477 controls); b) a continuous measure of autism-related traits, the Social Responsiveness Scale (SRS, among 1,272 cases and controls); and c) a measure of autism severity, the Calibrated Severity Score (among 1,380 cases). In addition to the individual's air toxic level, mixed models (clustering on family) included the family mean air toxic level, birth year, and census covariates, with consideration of the false discovery rate. RESULTS: ASD diagnosis was positively associated with propionaldehyde, methyl tert-butyl ether (MTBE), bromoform, 1,4-dioxane, dibenzofurans, and glycol ethers and was inversely associated with 1,4-dichlorobenzene, 4,4'-methylene diphenyl diisocyanate (MDI), benzidine, and ethyl carbamate (urethane). These associations were robust to adjustment in two-pollutant models. Autism severity was associated positively with carbon disulfide and chlorobenzene, and negatively with 1,4-dichlorobenzene. There were no associations with the SRS. CONCLUSIONS: Some air toxics were associated with ASD risk and severity, including some traffic-related air pollutants and newly-reported associations, but other previously reported associations with metals and volatile organic compounds were not reproducible. https://doi.org/10.1289/EHP1867.

A Systematic Review and Meta-Analysis of Multiple Airborne Pollutants and Autism Spectrum Disorder.

BACKGROUND: Exposure to ambient air pollution is widespread and may be detrimental to human brain development and a potential risk factor for Autism Spectrum Disorder (ASD). We conducted a systematic review of the human evidence on the relationship between ASD and exposure to all airborne pollutants, including particulate matter air pollutants and others (e.g. pesticides and metals). OBJECTIVE: To answer the question: "is developmental exposure to air pollution associated with ASD?" METHODS: We conducted a comprehensive search of the literature, identified relevant studies using inclusion/exclusion criteria pre-specified in our protocol (registered in PROSPERO, CRD # 42015017890), evaluated the potential risk of bias for each included study and identified an appropriate subset of studies to combine in a meta-analysis. We then rated the overall quality and strength of the evidence collectively across all air pollutants. RESULTS: Of 1,158 total references identified, 23 human studies met our inclusion criteria (17 case-control, 4 ecological, 2 cohort). Risk of bias was generally low across studies for most domains; study limitations were related to potential confounding and accuracy of exposure assessment methods. We rated the quality of the body of evidence across all air pollutants as "moderate." From our meta-analysis, we found statistically significant summary odds ratios (ORs) of 1.07 (95% CI: 1.06, 1.08) per 10-µg/m3 increase in PM10 exposure (n = 6 studies) and 2.32 (95% CI: 2.15, 2.51) per 10-µg/m3 increase in PM2.5 exposure (n = 3 studies). For pollutants not included in a meta-analysis, we collectively evaluated evidence from each study in rating the strength and quality of overall evidence considering factors such as inconsistency, imprecision, and evidence of dose-response. All included studies generally showed increased risk of ASD with increasing exposure to air pollution, although not consistently across all chemical components. CONCLUSION: After considering strengths and limitations of the body of research, we concluded that there is "limited evidence of toxicity" for the association between early life exposure to air pollution as a whole and diagnosis of ASD. The strongest evidence was between prenatal exposure to particulate matter and ASD. However, the small number of studies in the meta-analysis and unexplained statistical heterogeneity across the individual study estimates means that the effect could be larger or smaller (including not significant) than these studies estimate. Our research supports the need for health protective public policy to reduce exposures to harmful airborne contaminants among pregnant women and children and suggests opportunities for optimizing future research.

Of decrements and disorders: assessing impairments in neurodevelopment in prospective studies of environmental toxicant exposures.

Prenatal and early life neurodevelopment is exquisitely sensitive to insult from environmental exposures. Identifying the effects of environmental toxicants on neurodevelopmental disorders is particularly important from a public health perspective because many of these exposures are modifiable and may be targeted for intervention. Studying these associations in prospective cohort studies that measure quantitative, dimensional traits related to neurodevelopmental disorders, using standardized instruments such as psychometric tests or rating scales, mitigates many of the challenges that arise when studying clinically diagnosed disorders. We consider validity and feasibility impacts resulting from this design approach, including: 1) enhanced prospective exposure assessment with high quality environmental measures during developmentally relevant windows; 2) reduced bias because studies of continuous outcomes do not recruit cases and controls and are therefore not vulnerable to control selection bias; 3) enhanced statistical power because traits are measured on all individuals in the cohort and power is not limited by the number of cases; 4) reduced outcome misclassification because measuring quantitative traits avoids lumping together individuals with very heterogeneous phenotypes into one category. We use autism spectrum disorders (ASD) as an example to illustrate the advantages of this approach. Investigating the determinants of neurodevelopmental disorders - particularly modifiable determinants such as environmental toxicant exposures - is of great public health importance, given the apparent substantial rise of disorders like ASD over the past few decades. The use of prospective designs measuring quantitative, dimensional traits offers a powerful opportunity to provide important clues to the etiology of these disorders and is likely to accelerate our understanding of the role of environmental toxicant exposures as risk factors.

Particulate matter exposure, prenatal and postnatal windows of susceptibility, and autism spectrum disorders.

BACKGROUND: Recent studies suggest that exposure to traffic-related air pollutants, including particulate matter (PM), is associated with autism spectrum disorder (autism). METHODS: Children with autism were identified by records-based surveillance (n = 645 born in North Carolina in 1994, 1996, 1998, or 2000, and n = 334 born in the San Francisco Bay Area in California in 1996). They were compared with randomly sampled children born in the same counties and years identified from birth records (n = 12,434 in North Carolina and n = 2,232 in California). Exposure to PM less than 10 µm (PM10) at the birth address was assigned to each child by a geostatistical interpolation method using daily concentrations from air pollution regulatory monitors. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) for a 10 µg/m increase in PM10 within 3-month periods from preconception through the child's first birthday, adjusting for year, state, maternal education and age, race/ethnicity, and neighborhood-level urbanization and median household income, and including a nonparametric term for week of birth to account for seasonal trends. RESULTS: Temporal patterns in PM10 were pronounced, leading to an inverse correlation between the first- and third-trimester concentrations (r = -0.7). Adjusted ORs were, for the first trimester, 0.86 (95% CI = 0.74-0.99), second trimester, 0.97 (0.83-1.15), and third trimester, 1.36 (1.13-1.63); and, after simultaneously including first- and third-trimester concentrations to account for the inverse correlation, were: first trimester, 1.01 (0.81-1.27) and third trimester, 1.38 (1.03-1.84). CONCLUSIONS: Our study adds to previous work in California showing a relation between traffic-related air pollution and autism, and adds similar findings in an eastern US state, with results consistent with increased susceptibility in the third-trimester.

Environmental chemical exposures and autism spectrum disorders: a review of the epidemiological evidence.

In the past decade, the number of epidemiological publications addressing environmental chemical exposures and autism has grown tremendously. These studies are important because it is now understood that environmental factors play a larger role in causing autism than previously thought and because they address modifiable risk factors that may open up avenues for the primary prevention of the disability associated with autism. In this review, we covered studies of autism and estimates of exposure to tobacco, air pollutants, volatile organic compounds and solvents, metals (from air, occupation, diet, dental amalgams, and thimerosal-containing vaccines), pesticides, and organic endocrine-disrupting compounds such as flame retardants, non-stick chemicals, phthalates, and bisphenol A. We included studies that had individual-level data on autism, exposure measures pertaining to pregnancy or the 1st year of life, valid comparison groups, control for confounders, and adequate sample sizes. Despite the inherent error in the measurement of many of these environmental exposures, which is likely to attenuate observed associations, some environmental exposures showed associations with autism, especially traffic-related air pollutants, some metals, and several pesticides, with suggestive trends for some volatile organic compounds (e.g., methylene chloride, trichloroethylene, and styrene) and phthalates. Whether any of these play a causal role requires further study. Given the limited scope of these publications, other environmental chemicals cannot be ruled out, but have not yet been adequately studied. Future research that addresses these and additional environmental chemicals, including their most common routes of exposures, with accurate exposure measurement pertaining to several developmental windows, is essential to guide efforts for the prevention of the neurodevelopmental damage that manifests in autism symptoms.